Organic light-emitting diode (OLED) technology is considered as a promising alternative to mobile displays. This paper explores how to reduce the OLED power consumption by exploiting visual attention. First, we model the problem of OLED image scaling optimization, with the objective of minimizing the power required to display an image without adversely impacting the user’s visual experience. Then, we propose an algorithm to solve the fundamental problem, and prove its optimality even without the accurate power model. Finally, based on the algorithm, we consider implementation issues and realize two application scenarios on a commercial OLED mobile tablet. The results of experiments conducted on the tablet with real images demonstrate that the proposed methodology can achieve significant power savings while retaining the visual quality.
1. Catch Your Attention:
Quality-Retaining Power Saving
on Mobile OLED Displays
Chun-Han Lin, Chih-Kai Kang, and Pi-Cheng Hsiu
Research Center for IT Innovation, Academia Sinica
This work was presented at IEEE/ACM DAC 2014
2. Motivation
• OLED is deemed a promising technology to
replace LCD for mobile displays
– Many nice features
– Black image (≃ 0 power) vs. White image (2xLCD
power)
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3. Low-Power Techniques for OLED
Displays
• Partial display disabling or dimming
– Darken the contents Impact user perception
• Color remapping
– Use other colors instead Not applicable to natural
images
• OLED dynamic voltage scaling
– Decrease the supply voltage HW support &
rectangular regions
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4. Inspired by Human Visual Attention
• Different regions in an image
– Receive varying degrees of visual attention
– Can tolerate different degrees of image distortion
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5. Quality-Retaining Power Saving
• Image pixel scaling
– Scale down the pixel values in regions of any shape
• Technical problems
– How to segment an image into regions?
– How to determine an appropriate scaling ratio for each
region?
• Contributions
– Link human visual attention to OLED power saving
– Develop an optimal algorithm w/o accurate power
models
– Implement two application scenarios on tablets
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6. 6
Fast and optimal without
accurate OLED power models
Distortion
(SSIM)
Analysis
Attention (Itti)
Perception
(JND)
Conversion
Optimal
Algorithm
7. Experiment Setup
• 4 images on Samsung Galaxy Tab 7.7
– Different characteristics in terms of luminance and saliency
– Performance Metrics
- Execution time (second) and power consumption (watt)
– Comparison
- A grid-based approach [DAC’12]
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8. Experiment Results –
Impact of Tunable Parameters
• Image Distortion
– 38-42% when the distortion
threshold is set at 0.94
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• Number of regions
– 38-42% when the number of
regions is set at 5
9. Experiment Results –
GRID vs. CURA
• Execution time (seconds)
• Power consumption (watts)
• Visual quality
– See a video demo
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GRID CURA
Image Converter 27~219 7.6~8.8
Power-Saving Mode 0.97~4.77 0.72~0.811
GRID CURA
Image Converter 237~648 284~572
Power-Saving Mode 362~797 305~595
*PSM uses Lanczos resampling to scale down the resolution for speedup at a cost of less power saving.
10. Conclusion
• We introduce visual attention into the quality-retaining
power-saving design on mobile OLED displays
• We present CURA to realize the notion and have
implemented two application scenarios
– Samsung Galaxy Tab 7.7 can save 38-42% OLED power
while retaining visual quality
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Please come to my poster for more details!